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This book discusses comprehensively the advanced manufacturing processes, including illustrative examples of the processes, mathematical modeling, and the need to optimize associated parameter problems. In addition, it describes in detail the cohort intelligence methodology and its variants along with illustrations, to help readers gain a better understanding of the framework. The theoretical and statistical rigor is validated by comparing the solutions with evolutionary algorithms, simulation annealing, response surface methodology, the firefly algorithm, and experimental work. Lastly, the book critically reviews several socio-inspired optimization methods.
| Autorius: | Apoorva Shastri, Anand J. Kulkarni, Aniket Nargundkar, |
| Serija: | Springer Series in Advanced Manufacturing |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2020 |
| Knygos puslapių skaičius: | 140 |
| ISBN-10: | 981157796X |
| ISBN-13: | 9789811577963 |
| Formatas: | 241 x 160 x 14 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Socio-Inspired Optimization Methods for Advanced Manufacturing Processes“
